A Cross-Sectional Characterization of Insulin Resistance by Phenotype and Insulin Clamp in East Asian Americans with Type 1 and Type 2 Diabetes

Classic features of type 1 and type 2 diabetes may not apply in Asian Americans, due to shared absence of common HLA DR-DQ genotype, low prevalence of positive anti-islet antibodies and low BMI in both types of diabetes. Our objective was to characterize diabetic phenotypes in Asian Americans by clamp and clinical features.This was a cross-sectional study conducted in a referral center. Thirty East young Asian American adult volunteers (27.6±5.5 years) with type 1, type 2 diabetes or controls underwent hyperinsulinemic euglycemic clamp to assess insulin resistance and DEXA to assess adiposity.Gender, BMI, waist/hip ratio, leptin, LDL, anti-GAD, anti-IA2 antibodies and C-reactive protein were similar among three groups. Serum C-peptide, adiponectin, free fatty acid, HDL concentrations and truncal fat by DEXA, were different between diabetic groups. Glucose disposal rate by clamp was lowest in type 2 diabetes, followed by type 1 diabetes and controls (5.43±2.70, 7.62±2.59, 8.61±2.37 mg/min/kg, respectively, p = 0.001). Free fatty acid concentration universally plummeted during steady state of the clamp procedure regardless of diabetes types in all three groups. Adipocyte fatty acid binding protein in the entire cohort (r = -0.625, p = 0.04) and controls (r = -0.869, p = 0.046) correlated best with insulin resistance, independent of BMI.Type 2 diabetes in Asian Americans was associated with insulin resistance despite having low BMI as type 1 diabetes, suggesting a potential role for targeting insulin resistance apart from weight loss. Adipocyte fatty acid binding protein, strongly associated with insulin resistance, independent of adiposity in the young Asian American population, may potentially serve as a biomarker to identify at-risk individuals. Larger studies are needed to confirm this finding

Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

Background. Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Conclusion. Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis. © 2008 Scotch et al; licensee BioMed Central Ltd

Observation of unidirectional backscattering-immune topological electromagnetic states

One of the most striking phenomena in condensed-matter physics is the quantum Hall effect, which arises in two-dimensional electron systems subject to a large magnetic field applied perpendicular to the plane in which the electrons reside. In such circumstances, current is carried by electrons along the edges of the system, in so-called chiral edge states (CESs). These are states that, as a consequence of nontrivial topological properties of the bulk electronic band structure, have a unique directionality and are robust against scattering from disorder. Recently, it was theoretically predicted that electromagnetic analogues of such electronic edge states could be observed in photonic crystals, which are materials having refractive-index variations with a periodicity comparable to the wavelength of the light passing through them. Here we report the experimental realization and observation of such electromagnetic CESs in a magneto-optical photonic crystal fabricated in the microwave regime. We demonstrate that, like their electronic counterparts, electromagnetic CESs can travel in only one direction and are very robust against scattering from disorder; we find that even large metallic scatterers placed in the path of the propagating edge modes do not induce reflections. These modes may enable the production of new classes of electromagnetic device and experiments that would be impossible using conventional reciprocal photonic states alone. Furthermore, our experimental demonstration and study of photonic CESs provides strong support for the generalization and application of topological band theories to classical and bosonic systems, and may lead to the realization and observation of topological phenomena in a generally much more controlled and customizable fashion than is typically possible with electronic systems

Propentofylline Targets TROY, a Novel Microglial Signaling Pathway

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain cancer, with a median survival of less than 2 years after diagnosis with current available therapies. The tumor microenvironment serves a critical role in tumor invasion and progression, with microglia as a critical player. Our laboratory has previously demonstrated that propentofylline, an atypical methylxanthine with central nervous system glial modulating and anti-inflammatory actions, significantly decreases tumor growth in a GBM rodent model by preferentially targeting microglia. In the present study, we used the CNS-1 rat glioma model to elucidate the mechanisms of propentofylline. Here we demonstrate that propentofylline targets TROY, a novel signaling molecule up-regulated in infiltrating microglia, and not macrophages, in response to CNS-1 cells. We identify Pyk2, Rac1 and pJNK as the downstream signaling molecules of TROY through western blot analysis and siRNA transfection. We demonstrate that inhibition of TROY expression in microglia by siRNA transfection significantly inhibits microglial migration towards CNS-1 cells similar to 10 µM propentofylline treatment. These results identify TROY as a novel molecule expressed in microglia, involved in their migration and targeted by propentofylline. Furthermore, these results describe a signaling molecule that is differentially expressed between microglia and macrophages in the tumor microenvironment

Structural diversity of supercoiled DNA

By regulating access to the genetic code, DNA supercoiling strongly affects DNA metabolism. Despite its importance, however, much about supercoiled DNA (positively supercoiled DNA, in particular) remains unknown. Here we use electron cryo-tomography together with biochemical analyses to investigate structures of individual purified DNA min icircle topoisomers with defined degrees of supercoiling. Our results reveal that each topoisomer, negative or positive, adopts a unique and surprisingly wide distribution of three-dimensional conformations. Moreover, we uncover striking differences in how the topoisomers handle torsional stress. As negative supercoiling increases, bases are increasingly exposed. Beyond a sharp supercoiling threshold, we also detect exposed bases in positively supercoiled DNA. Molecular dynamics simulations independently confirm the conformational heterogeneity and provide atomistic insight into the flexibility of supercoiled DNA. Our integrated approach reveals the three-dimensional structures of DNA that are essential for its function

MoVam7, a Conserved SNARE Involved in Vacuole Assembly, Is Required for Growth, Endocytosis, ROS Accumulation, and Pathogenesis of Magnaporthe oryzae

Soluble NSF attachment protein receptor (SNARE) proteins play a central role in membrane fusion and vesicle transport of eukaryotic organisms including fungi. We previously identified MoSce22 as a homolog of Saccharomyces cerevisiae SNARE protein Sec22 to be involved in growth, stress resistance, and pathogenicity of Magnaporthe oryzae. Here, we provide evidences that MoVam7, an ortholog of S. cerevisiae SNARE protein Vam7, exerts conserved functions in vacuolar morphogenesis and functions in pathogenicity of M. oryzae. Staining with neutral red and FM4-64 revealed the presence of abnormal fragmented vacuoles and an absence of the Spitzenkörper body in the ΔMovam7 mutant. The ΔMovam7 mutant also exhibited reduced vegetative growth, poor conidiation, and failure to produce the infection structure appressorium. Additionally, treatments with cell wall perturbing agents indicated weakened cell walls and altered distributions of the cell wall component chitin. Furthermore, the ΔMovam7 mutant showed a reduced accumulation of reactive oxygen species (ROS) in the hyphal apex and failed to cause diseases on the rice plant. In summary, our studies indicate that MoVam7, like MoSec22, is a component of the SNARE complex whose functions in vacuole assembly also underlies the growth, conidiation, appressorium formation, and pathogenicity of M. oryzae. Further studies of MoVam7, MoSec22, and additional members of the SNARE complex are likely to reveal critical mechanisms in vacuole formation and membrane trafficking that is linked to fungal pathogenicity

Molecular dynamics of ribosomal elongation factors G and Tu

Translation on the ribosome is controlled by external factors. During polypeptide lengthening, elongation factors EF-Tu and EF-G consecutively interact with the bacterial ribosome. EF-Tu binds and delivers an aminoacyl-tRNA to the ribosomal A site and EF-G helps translocate the tRNAs between their binding sites after the peptide bond is formed. These processes occur at the expense of GTP. EF-Tu:tRNA and EF-G are of similar shape, share a common binding site, and undergo large conformational changes on interaction with the ribosome. To characterize the internal motion of these two elongation factors, we used 25 ns long all-atom molecular dynamics simulations. We observed enhanced mobility of EF-G domains III, IV, and V and of tRNA in the EF-Tu:tRNA complex. EF-Tu:GDP complex acquired a configuration different from that found in the crystal structure of EF-Tu with a GTP analogue, showing conformational changes in the switch I and II regions. The calculated electrostatic properties of elongation factors showed no global similarity even though matching electrostatic surface patches were found around the domain I that contacts the ribosome, and in the GDP/GTP binding region

A second generation human haplotype map of over 3.1 million SNPs

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r(2) of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r(2) of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62863/1/nature06258.pd

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

Background: The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings: Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance: We propose a new neural model for MT pattern computation and motion disambiguation that i